EconPapers    
Economics at your fingertips  
 

Global exponential stability of impulsive Cohen–Grossberg neural networks with delays

Wenpin Luo, Shouming Zhong and Jun Yang

Chaos, Solitons & Fractals, 2009, vol. 42, issue 2, 1084-1091

Abstract: In this paper, a class of Cohen–Grossberg neural networks involving delays and impulsive effects is considered. The analysis exploits a homeomorphism mapping and an appropriate Lyapunov functional, to derive easily verifiable sufficient conditions for convergence to the unique globally exponentially stable equilibrium state. The proposed conditions generalize some previous results in the literature. At last, two numerical examples are worked out to illustrate the effectiveness of our results.

Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077909001258
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:42:y:2009:i:2:p:1084-1091

DOI: 10.1016/j.chaos.2009.03.046

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().

 
Page updated 2025-03-19
Handle: RePEc:eee:chsofr:v:42:y:2009:i:2:p:1084-1091